Novice and professional photographers alike are drawn to digital cameras by their many advantages over conventional film cameras. For instance, digital cameras allow a photographer to readily capture, review, and keep or delete multiple digital images of a scene in virtually real time. However, for non-professional photographers, it is still difficult to optimally capture a moment on a consistent basis even using digital cameras. Factors that may contribute to the “imperfection” of captured images include sensor limitations and inappropriate camera settings.
Many cameras have pre-defined categories of camera settings (e.g., portrait, landscape, close-up, etc.) that a photographer may select for a given scene type. By selecting a category suitable for a given scene prior to capturing an image, the camera is automatically adjusted to the pre-determined settings for that category of images.
In practice, these categories do not adequately cover all scenes. For example, a photographer may wish to capture a subject 5 feet away from the camera as well as the landscape 1000 feet behind the subject. In this case, it is inappropriate for the photographer to select either the portrait or landscape mode.
Even when a scene roughly falls within a category, the captured image may still be “imperfect” due to factors particular to that scene. For example, a portrait subject could be so strongly illuminated from behind that the halo around the subject confuses the camera, so that the flash-fill feature is not triggered. As a result, the subject will be underexposed.
Often, by the time the photographer realizes that the captured images are not quite right, the moment she wishes to capture has already passed.
Thus, a market exists for digital photography processes and devices that can automatically provide (e.g., by capturing or synthesizing) more optimized digital images.